OpenAI launches a fast decisions API aimed at cheap agent classification
Fast, cheap choice-models just got a frontier-lab endorsement; agent-monitoring economics may shift, but real performance is unverified.
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OpenAI announced a limited preview of its Decisions API at DevDay on September 29: the Luna model picks quickly from a predefined set of options.
CEO Sam Altman said focusing the model on that choice makes it extremely fast while keeping image understanding, broad language support and safety protections. It closely resembles Jev, released by TypeSafe AI earlier this month — a fast classifier that outputs probabilities, which developers already use to make LLM pipelines faster and cheaper.
One direct application is agent monitoring: QueryStory's Shapor Naghibzadeh built a hackathon demo using Jev to check each agentic action, saying the same review would cost $2.94 with Jev versus $372 with a frontier LLM. Decisions API remains a limited preview with no developer benchmarks yet, and how well these models' outputs are calibrated is the key open question.